Research Interests
My research spans Monte Carlo modeling of ionizing radiation, medical imaging, and the application of deep learning in healthcare. I focus on areas such as computing interaction coefficients, exploring novel shielding materials, and developing AI-driven methods for tumor detection. Specifically, my work includes deep learning approaches for automatic detection and classification of breast and brain tumors, as well as personalized dosimetry models for nuclear medicine and radiotherapy. Through these efforts, I aim to advance precision in computational physics and healthcare technologies.
Publications
Here is a list of my most recent papers.
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Comparison of Photon Interaction Coefficients for Tumor Compositions and Healthy Tissues
DOI 10.1088/1748-0221/19/07/P07035 -
A Mask R-CNN approach for detection and classification of brain tumors from MR images
DOI 10.1080/21681163.2023.2301391 -
A personalized Monte Carlo study of tumor and critical organ doses for trans-arterial radioembolization patients
DOI 10.1088/1361-6560/acf7a7 -
The use of computerized tomography (CT) and image processing for evaluation of the properties of
foam concrete produced with different content of foaming agent and aggregate
DOI 10.1016/j.conbuildmat.2023.132433 -
A deep learning approach for automatic detection, segmentation and classification of breast lesions from thermal images
DOI 10.1016/j.eswa.2022.118774